Google AI and Google Vertex AI Integration

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Orchestrate Google AI models within Google Vertex AI pipelines. Latenode's visual editor makes it easier to combine AI with custom logic. Scale complex AI workflows affordably and connect any API with ease.

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Google AI

Google Vertex AI

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google AI and Google Vertex AI

Create a New Scenario to Connect Google AI and Google Vertex AI

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google AI or Google Vertex AI will be your first step. To do this, click "Choose an app," find Google AI or Google Vertex AI, and select the appropriate trigger to start the scenario.

Add the Google AI Node

Select the Google AI node from the app selection panel on the right.

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Configure the Google AI

Click on the Google AI node to configure it. You can modify the Google AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Run node once

Add the Google Vertex AI Node

Next, click the plus (+) icon on the Google AI node, select Google Vertex AI from the list of available apps, and choose the action you need from the list of nodes within Google Vertex AI.

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Authenticate Google Vertex AI

Now, click the Google Vertex AI node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Vertex AI settings. Authentication allows you to use Google Vertex AI through Latenode.

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Configure the Google AI and Google Vertex AI Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Google Vertex AI Oauth 2.0

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Run node once

Set Up the Google AI and Google Vertex AI Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Google AI, Google Vertex AI, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Google AI and Google Vertex AI integration works as expected. Depending on your setup, data should flow between Google AI and Google Vertex AI (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Google AI and Google Vertex AI

Google Sheets + Google Vertex AI + Google Sheets: When a new row with customer feedback is added to Google Sheets, Vertex AI analyzes the text for sentiment. The sentiment score is then added to a new column in the same Google Sheet.

Google Vertex AI + Google AI + Slack: After Google Vertex AI model training, the results are sent to Google AI to generate a summary of the findings. This summary is then sent to a designated Slack channel to alert relevant engineers.

Google AI and Google Vertex AI integration alternatives

About Google AI

Use Google AI in Latenode to add smarts to your workflows. Process text, translate languages, or analyze images automatically. Unlike direct API calls, Latenode lets you combine AI with other apps, add logic, and scale without code. Automate content moderation, sentiment analysis, and more.

About Google Vertex AI

Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.

See how Latenode works

FAQ Google AI and Google Vertex AI

How can I connect my Google AI account to Google Vertex AI using Latenode?

To connect your Google AI account to Google Vertex AI on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google AI and click on "Connect".
  • Authenticate your Google AI and Google Vertex AI accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I analyze customer support tickets using both AI models?

Yes, you can! Latenode lets you chain Google AI and Google Vertex AI, automatically routing tickets for sentiment analysis and advanced issue classification, improving resolution times.

What types of tasks can I perform by integrating Google AI with Google Vertex AI?

Integrating Google AI with Google Vertex AI allows you to perform various tasks, including:

  • Creating personalized product recommendations based on user behavior data.
  • Automating content generation for marketing campaigns using advanced models.
  • Building a sophisticated chatbot for customer service with intelligent responses.
  • Analyzing large datasets to extract key insights and predict market trends.
  • Enhancing image recognition capabilities for quality control processes.

How does Latenode handle errors between Google AI and Vertex AI?

Latenode offers built-in error handling, retry mechanisms, and detailed logging, ensuring robust workflows even with API issues.

Are there any limitations to the Google AI and Google Vertex AI integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Rate limits on the Google AI and Google Vertex AI APIs still apply.
  • Complex workflows with extensive data transformations might require more processing time.
  • Some advanced features of Google Vertex AI may require custom code using JavaScript.

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